mj-v7-edit 接口
curl --request POST \
--url https://api.evolink.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "mj-v7-edit",
"prompt": "美丽的山景背景",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 0,
"canvas": {
"width": 1024,
"height": 1024
},
"img_pos": {
"width": 512,
"height": 512,
"x": 256,
"y": 256
},
"speed": "fast"
}
}
'import requests
url = "https://api.evolink.ai/v1/images/generations"
payload = {
"model": "mj-v7-edit",
"prompt": "美丽的山景背景",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 0,
"canvas": {
"width": 1024,
"height": 1024
},
"img_pos": {
"width": 512,
"height": 512,
"x": 256,
"y": 256
},
"speed": "fast"
}
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
model: 'mj-v7-edit',
prompt: '美丽的山景背景',
model_params: {
task_id: 'task-unified-xxx',
image_number: 0,
canvas: {width: 1024, height: 1024},
img_pos: {width: 512, height: 512, x: 256, y: 256},
speed: 'fast'
}
})
};
fetch('https://api.evolink.ai/v1/images/generations', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.evolink.ai/v1/images/generations",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'model' => 'mj-v7-edit',
'prompt' => '美丽的山景背景',
'model_params' => [
'task_id' => 'task-unified-xxx',
'image_number' => 0,
'canvas' => [
'width' => 1024,
'height' => 1024
],
'img_pos' => [
'width' => 512,
'height' => 512,
'x' => 256,
'y' => 256
],
'speed' => 'fast'
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.evolink.ai/v1/images/generations"
payload := strings.NewReader("{\n \"model\": \"mj-v7-edit\",\n \"prompt\": \"美丽的山景背景\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0,\n \"canvas\": {\n \"width\": 1024,\n \"height\": 1024\n },\n \"img_pos\": {\n \"width\": 512,\n \"height\": 512,\n \"x\": 256,\n \"y\": 256\n },\n \"speed\": \"fast\"\n }\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api.evolink.ai/v1/images/generations")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"model\": \"mj-v7-edit\",\n \"prompt\": \"美丽的山景背景\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0,\n \"canvas\": {\n \"width\": 1024,\n \"height\": 1024\n },\n \"img_pos\": {\n \"width\": 512,\n \"height\": 512,\n \"x\": 256,\n \"y\": 256\n },\n \"speed\": \"fast\"\n }\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.evolink.ai/v1/images/generations")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"model\": \"mj-v7-edit\",\n \"prompt\": \"美丽的山景背景\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0,\n \"canvas\": {\n \"width\": 1024,\n \"height\": 1024\n },\n \"img_pos\": {\n \"width\": 512,\n \"height\": 512,\n \"x\": 256,\n \"y\": 256\n },\n \"speed\": \"fast\"\n }\n}"
response = http.request(request)
puts response.read_body{
"created": 1757165031,
"id": "task-unified-1757165031-mjv7",
"model": "<string>",
"object": "image.generation.task",
"progress": 0,
"status": "pending",
"task_info": {
"can_cancel": true,
"estimated_time": 45
},
"type": "image",
"usage": {
"billing_rule": "per_call",
"credits_reserved": 1.8,
"user_group": "default"
}
}{
"error": {
"code": "invalid_request",
"message": "Invalid request parameters",
"type": "invalid_request_error"
}
}{
"error": {
"code": "unauthorized",
"message": "Invalid or expired token",
"type": "authentication_error"
}
}{
"error": {
"code": "insufficient_quota",
"message": "Insufficient quota. Please top up your account.",
"type": "insufficient_quota"
}
}{
"error": {
"code": "model_access_denied",
"message": "Token does not have access to model: mj-v7-edit",
"type": "invalid_request_error"
}
}{
"error": {
"code": "rate_limit_exceeded",
"message": "Too many requests, please try again later",
"type": "rate_limit_error"
}
}{
"error": {
"code": "internal_error",
"message": "Internal server error",
"type": "api_error"
}
}Midjourney V7
Midjourney V7 画布编辑
- 在画布上重新定位已生成的图片,并用 AI 填充空白区域
- 适用于调整构图、扩展场景等
- 异步处理模式,使用返回的任务ID 进行查询
POST
/
v1
/
images
/
generations
mj-v7-edit 接口
curl --request POST \
--url https://api.evolink.ai/v1/images/generations \
--header 'Authorization: Bearer <token>' \
--header 'Content-Type: application/json' \
--data '
{
"model": "mj-v7-edit",
"prompt": "美丽的山景背景",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 0,
"canvas": {
"width": 1024,
"height": 1024
},
"img_pos": {
"width": 512,
"height": 512,
"x": 256,
"y": 256
},
"speed": "fast"
}
}
'import requests
url = "https://api.evolink.ai/v1/images/generations"
payload = {
"model": "mj-v7-edit",
"prompt": "美丽的山景背景",
"model_params": {
"task_id": "task-unified-xxx",
"image_number": 0,
"canvas": {
"width": 1024,
"height": 1024
},
"img_pos": {
"width": 512,
"height": 512,
"x": 256,
"y": 256
},
"speed": "fast"
}
}
headers = {
"Authorization": "Bearer <token>",
"Content-Type": "application/json"
}
response = requests.post(url, json=payload, headers=headers)
print(response.text)const options = {
method: 'POST',
headers: {Authorization: 'Bearer <token>', 'Content-Type': 'application/json'},
body: JSON.stringify({
model: 'mj-v7-edit',
prompt: '美丽的山景背景',
model_params: {
task_id: 'task-unified-xxx',
image_number: 0,
canvas: {width: 1024, height: 1024},
img_pos: {width: 512, height: 512, x: 256, y: 256},
speed: 'fast'
}
})
};
fetch('https://api.evolink.ai/v1/images/generations', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://api.evolink.ai/v1/images/generations",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
CURLOPT_POSTFIELDS => json_encode([
'model' => 'mj-v7-edit',
'prompt' => '美丽的山景背景',
'model_params' => [
'task_id' => 'task-unified-xxx',
'image_number' => 0,
'canvas' => [
'width' => 1024,
'height' => 1024
],
'img_pos' => [
'width' => 512,
'height' => 512,
'x' => 256,
'y' => 256
],
'speed' => 'fast'
]
]),
CURLOPT_HTTPHEADER => [
"Authorization: Bearer <token>",
"Content-Type: application/json"
],
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"strings"
"net/http"
"io"
)
func main() {
url := "https://api.evolink.ai/v1/images/generations"
payload := strings.NewReader("{\n \"model\": \"mj-v7-edit\",\n \"prompt\": \"美丽的山景背景\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0,\n \"canvas\": {\n \"width\": 1024,\n \"height\": 1024\n },\n \"img_pos\": {\n \"width\": 512,\n \"height\": 512,\n \"x\": 256,\n \"y\": 256\n },\n \"speed\": \"fast\"\n }\n}")
req, _ := http.NewRequest("POST", url, payload)
req.Header.Add("Authorization", "Bearer <token>")
req.Header.Add("Content-Type", "application/json")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://api.evolink.ai/v1/images/generations")
.header("Authorization", "Bearer <token>")
.header("Content-Type", "application/json")
.body("{\n \"model\": \"mj-v7-edit\",\n \"prompt\": \"美丽的山景背景\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0,\n \"canvas\": {\n \"width\": 1024,\n \"height\": 1024\n },\n \"img_pos\": {\n \"width\": 512,\n \"height\": 512,\n \"x\": 256,\n \"y\": 256\n },\n \"speed\": \"fast\"\n }\n}")
.asString();require 'uri'
require 'net/http'
url = URI("https://api.evolink.ai/v1/images/generations")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
request["Authorization"] = 'Bearer <token>'
request["Content-Type"] = 'application/json'
request.body = "{\n \"model\": \"mj-v7-edit\",\n \"prompt\": \"美丽的山景背景\",\n \"model_params\": {\n \"task_id\": \"task-unified-xxx\",\n \"image_number\": 0,\n \"canvas\": {\n \"width\": 1024,\n \"height\": 1024\n },\n \"img_pos\": {\n \"width\": 512,\n \"height\": 512,\n \"x\": 256,\n \"y\": 256\n },\n \"speed\": \"fast\"\n }\n}"
response = http.request(request)
puts response.read_body{
"created": 1757165031,
"id": "task-unified-1757165031-mjv7",
"model": "<string>",
"object": "image.generation.task",
"progress": 0,
"status": "pending",
"task_info": {
"can_cancel": true,
"estimated_time": 45
},
"type": "image",
"usage": {
"billing_rule": "per_call",
"credits_reserved": 1.8,
"user_group": "default"
}
}{
"error": {
"code": "invalid_request",
"message": "Invalid request parameters",
"type": "invalid_request_error"
}
}{
"error": {
"code": "unauthorized",
"message": "Invalid or expired token",
"type": "authentication_error"
}
}{
"error": {
"code": "insufficient_quota",
"message": "Insufficient quota. Please top up your account.",
"type": "insufficient_quota"
}
}{
"error": {
"code": "model_access_denied",
"message": "Token does not have access to model: mj-v7-edit",
"type": "invalid_request_error"
}
}{
"error": {
"code": "rate_limit_exceeded",
"message": "Too many requests, please try again later",
"type": "rate_limit_error"
}
}{
"error": {
"code": "internal_error",
"message": "Internal server error",
"type": "api_error"
}
}Midjourney 内置内容审核机制。如果生成的部分图像触发了审核过滤,该次请求已消耗的积分将无法退还,请留意提示词的内容合规性。
授权
##所有接口均需要使用Bearer Token进行认证##
获取 API Key :
访问 API Key 管理页面 获取您的 API Key
使用时在请求头中添加:
Authorization: Bearer YOUR_API_KEY请求体
application/json
模型名称
可用选项:
mj-v7-edit 示例:
"mj-v7-edit"
描述期望填充的内容
示例:
"美丽的山景背景"
画布编辑参数
Show child attributes
Show child attributes
任务完成后的HTTPS回调地址
回调时机:
- 任务完成(completed)、失败(failed)或取消(cancelled)时触发
- 在计费确认完成后发送
安全限制:
- 仅支持HTTPS协议
- 禁止回调到内网IP地址(127.0.0.1、10.x.x.x、172.16-31.x.x、192.168.x.x等)
- URL长度不超过
2048字符
回调机制:
- 超时时间:
10秒 - 失败后最多重试
3次(会分别在失败的1秒/2秒/4秒后进行重试) - 回调响应体格式与任务查询接口返回的格式一致
- 回调地址若返回2xx状态码视为成功,其他状态码会触发重试
示例:
"https://your-domain.com/webhooks/image-task-completed"
响应
图像生成任务创建成功
任务创建时间戳
示例:
1757165031
任务ID
示例:
"task-unified-1757165031-mjv7"
实际使用的模型名称
任务的具体类型
可用选项:
image.generation.task 任务进度百分比 (0-100)
必填范围:
0 <= x <= 100示例:
0
任务状态
可用选项:
pending, processing, completed, failed 示例:
"pending"
Show child attributes
Show child attributes
可用选项:
text, image, audio, video 示例:
"image"
Show child attributes
Show child attributes
⌘I